A Framework for High-Accuracy Privacy-Preserving Mining

To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of data records have been proposed recently. In this paper, we present a generalized matrix-theoretic model of random perturbation, which facilitates a systematic approach to the design of perturbation mechanisms for privacy-preserving mining. Specifically, we demonstrate that (a) the prior techniques differ only in their settings for the model parameters, and (b) through appropriate choice of parameter settings, we can derive new perturbation techniques that provide highly accurate mining results even under strict privacy guarantees. We also propose a novel perturbation mechanism wherein the model parameters are themselves characterized as random variables, and demonstrate that this feature provides significant improvements in privacy at a very marginal cost in accuracy. While our model is valid for random-perturbation-based privacy-preserving mining in general, we specifically evaluate its utility here with regard to frequent-itemset mining on a variety of real datasets. The experimental results indicate that our mechanisms incur substantially lower identity and support errors as compared to the prior techniques

A framework of privacy shield in organizational information systems

Preserving Privacy and the protection of personally identifiable information (PII) have been of increasing interest over the last few years. Many privacy advocates, and a significant portion of the general public, feared that the new initiatives used in an attempt to fight terrorism, would have a serious impact on an individual?s right and ability to protect their privacy. This paper proposes a new framework for Preserving Privacy for individuals along with the protection of personally identifiable information. We have termed it Privacy Shield. Through the application of anonymity and privacy principles in design, the privacy protecting separation of data, the use of public key infrastructure, and the application of our Information System Hippocratic Policies, we provide a framework of privacy shield to protect an information system user?s personal data

Privacy in the Genomic Era

Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) (i) an association with traits and certain diseases, (ii) identification capability (e.g., forensics), and (iii) revelation of family relationships. Moreover, direct-to-consumer DNA testing increases the likelihood that genome data will be made available in less regulated environments, such as the Internet and for-profit companies. The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy. While the computer scientists have addressed data privacy for various data types, there has been less attention dedicated to genomic data. Thus, the goal of this paper is to provide a systematization of knowledge for the computer science community. In doing so, we address some of the (sometimes erroneous) beliefs of this field and we report on a survey we conducted about genome data privacy with biomedical specialists. Then, after characterizing the genome privacy problem, we review the state-of-the-art regarding privacy attacks on genomic data and strategies for mitigating such attacks, as well as contextualizing these attacks from the perspective of medicine and public policy. This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward

An Approach for Managing Access to Personal Information Using Ontology-Based Chains

The importance of electronic healthcare has caused numerous changes in both substantive and procedural aspects of healthcare processes. These changes have produced new challenges to patient privacy and information secrecy. Traditional privacy policies cannot respond to rapidly increased privacy needs of patients in electronic healthcare. Technically enforceable privacy policies are needed in order to protect patient privacy in modern healthcare with its cross organisational information sharing and decision making. This thesis proposes a personal information flow model that specifies a limited number of acts on this type of information. Ontology classified Chains of these acts can be used instead of the "intended/business purposes" used in privacy access control to seamlessly imbuing current healthcare applications and their supporting infrastructure with security and privacy functionality. In this thesis, we first introduce an integrated basic architecture, design principles, and implementation techniques for privacy-preserving data mining systems. We then discuss the key methods of privacypreserving data mining systems which include four main methods: Role based access control (RBAC), Hippocratic database, Chain method and eXtensible Access Control Markup Language (XACML). We found out that the traditional methods suffer from two main problems: complexity of privacy policy design and the lack of context flexibility that is needed while working in critical situations such as the one we find in hospitals. We present and compare strategies for realising these methods. Theoretical analysis and experimental evaluation show that our new method can generate accurate data mining models and safe data access management while protecting the privacy of the data being mined. The experiments followed comparative kind of experiments, to show the ease of the design first and then follow real scenarios to show the context flexibility in saving personal information privacy of our investigated method

Challenge of guarding online privacy: role of privacy seals, government regulations and technological solutions

The state of privacy in the 21st century is a worldwide concern, given the Internet’s global reach. The privacy violation on the internet is a significant problem and internet users have a right to adequate privacy. New e-business technologies have increased the ability of online merchants to collect, monitor, target, profile, and even sell personal information about consumers to third parties. Governments, business houses and employers collect data and monitor people, but their practices often threaten an individual’s privacy. Because vast amount of data can be collected on the Internet and due to global ramifications, citizens worldwide have expressed concerns over increasing cases of privacy violations. Several privacy groups, all around the world, have joined hands to give a boost to privacy movement. Consumer privacy, therefore, has attracted the widespread attention of regulators across the globe. With the European Directive already in force, “trust seals” and “government regulations” are the two leading forces pushing for more privacy disclosures. Of course, privacy laws vary throughout the globe but, unfortunately, it has turned out to be the subject of legal contention between the European Union and the United States. The EU has adopted very strict laws to protect its citizens’ privacy, in sharp contrast, to ‘lax-attitude’ and ‘self-regulated’ law of the US. For corporations that collect and use personal information, now ignoring privacy legislative and regulatory warning signs can prove to be a costly mistake. An attempt has been made in this paper to summarize the privacy legislation prevalent in Australia, Canada, the US, the EU, India, Japan, Hong Kong, Malaysia and Singapore. It is expected that a growing number of countries will adopt privacy laws to foster e-commerce. Accountability for privacy and personal data protection needs to be a joint effort among governments, privacy commissioners, organizations and individuals themselves

Privacy preserving data mining

A fruitful direction for future data mining research will be the development of technique that incorporates privacy concerns. Specifically, we address the following question. Since the primary task in data mining is the development of models about aggregated data, can we develop accurate models without access to precise information in individual data records? We analyze the possibility of privacy in data mining techniques in two phasesrandomization and reconstruction. Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. To preserve client privacy in the data mining process, techniques based on random perturbation of data records are used. Suppose there are many clients, each having some personal information, and one server, which is interested only in aggregate, statistically significant, properties of this information. The clients can protect privacy of their data by perturbing it with a randomization algorithm and then submitting the randomized version. This approach is called randomization. The randomization algorithm is chosen so that aggregate properties of the data can be recovered with sufficient precision, while individual entries are significantly distorted. For the concept of using value distortion to protect privacy to be useful, we need to be able to reconstruct the original data distribution so that data mining techniques can be effectively utilized to yield the required statistics. Analysis Let xi be the original instance of data at client i. We introduce a random shift yi using randomization technique explained below. The server runs the reconstruction algorithm (also explained below) on the perturbed value zi = xi + yi to get an approximate of the original data distribution suitable for data mining applications. Randomization We have used the following randomizing operator for data perturbation: Given x, let R(x) be x+€ (mod 1001) where € is chosen uniformly at random in {-100…100}. Reconstruction of discrete data set P(X=x) = f X (x) ----Given P(Y=y) = F y (y) ---Given P (Z=z) = f Z (z) ---Given f (X/Z) = P(X=x | Z=z) = P(X=x, Z=z)/P (Z=z) = P(X=x, X+Y=Z)/ f Z (z) = P(X=x, Y=Z - X)/ f Z (z) = P(X=x)*P(Y=Z-X)/ f Z (z) = P(X=x)*P(Y=y)/ f Z (z) Results In this project we have done two aspects of privacy preserving data mining. The first phase involves perturbing the original data set using ‘randomization operator’ techniques and the second phase deals with reconstructing the randomized data set using the proposed algorithm to get an approximate of the original data set. The performance metrics like percentage deviation, accuracy and privacy breaches were calculated. In this project we studied the technical feasibility of realizing privacy preserving data mining. The basic promise was that the sensitive values in a user’s record will be perturbed using a randomizing function and an approximate of the perturbed data set be recovered using reconstruction algorithm

Analysis of Existing Privacy-aware Access Control for E-Commerce Application

Due to the growing use of the internet, more and more critical processes are running over the web such as e-commerce. Internet allows commerce and business between parties who are physically distant and do not know each other doing the transaction. For the effective operation of the web application and e-commerce applications, security is a key issue. Various aspects of security are relevant to e-commerce such as database security. The availability of e-commerce, user transactions are no longer bound to traditional office-centered environment, but it can be started virtually anywhere at any time. It was moving from closed environment to open environment. In this paper, we clearly define the privacy-aware access control requirements. We also investigated few existing access control in the context of this requirements. We build an assessment criteria in our comparison based on the requirements defined which we finally used it later as a guidelines to design an access control for e-commerce application

Complying with Data Handling Requirements in Cloud Storage Systems

In past years, cloud storage systems saw an enormous rise in usage. However, despite their popularity and importance as underlying infrastructure for more complex cloud services, today's cloud storage systems do not account for compliance with regulatory, organizational, or contractual data handling requirements by design. Since legislation increasingly responds to rising data protection and privacy concerns, complying with data handling requirements becomes a crucial property for cloud storage systems. We present PRADA, a practical approach to account for compliance with data handling requirements in key-value based cloud storage systems. To achieve this goal, PRADA introduces a transparent data handling layer, which empowers clients to request specific data handling requirements and enables operators of cloud storage systems to comply with them. We implement PRADA on top of the distributed database Cassandra and show in our evaluation that complying with data handling requirements in cloud storage systems is practical in real-world cloud deployments as used for microblogging, data sharing in the Internet of Things, and distributed email storage.Comment: 14 pages, 11 figures; revised manuscript, accepted for publication in IEEE Transactions on Cloud Computin

Method for registration of vaccines for covid 19, through nfc technology

Conferencia de la 8th Eighth International Virtual Conference on Biosignals, Images, and Instrumentation (ICBSII).In these times of pandemic caused by Covid-19, new ways of dealing with the effects of the virus emerge, for this reason multiple measures are being carried out with the intention of mitigating its effects in the event of a possible contagion, which is why vaccinations are being carried out massive in order to be able to defend oneself against potential contagions, in this work an application made using the NFC communication protocol that mobile devices have is shown, as a result the demonstration of the use of the application is presented, where it reflects the data to be entered and can be viewed from any device.Campus At